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		<citationkey>MaranaJain:2005:RiFiMa</citationkey>
		<title>Ridge-based fingerprint matching sing Hough Transform</title>
		<format>On-line</format>
		<year>2005</year>
		<date>9-12 Oct. 2005</date>
		<numberoffiles>1</numberoffiles>
		<size>614 KiB</size>
		<author>Marana, Aparecido Nilceu,</author>
		<author>Jain, Anil K.,</author>
		<affiliation>UNESP – Faculdade de Ciências – Departamento de Computação – Bauru – SP – Brazil</affiliation>
		<affiliation>Michigan State University – College of Engineering – East Lansing – Michigan - USA</affiliation>
		<editor>Rodrigues, Maria Andréia Formico,</editor>
		<editor>Frery, Alejandro César,</editor>
		<e-mailaddress>marana@msu.edu</e-mailaddress>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 18 (SIBGRAPI)</conferencename>
		<conferencelocation>Natal</conferencelocation>
		<booktitle>Proceedings</booktitle>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<transferableflag>1</transferableflag>
		<contenttype>External Contribution</contenttype>
		<tertiarytype>Full Paper</tertiarytype>
		<keywords>Fingerprint matching, ridge, Hough transform, biometrics.</keywords>
		<abstract>Despite the efficacy of minutia-based fingerprint matching techniques for good-quality images captured by optical sensors, minutia-based techniques do not often perform so well on poor-quality images or fingerprint images captured by small solid-state sensors. Solid-state fingerprint sensors are being increasingly deployed in a wide range of applications for user authentication purposes. Therefore, it is necessary to develop new fingerprint-matching techniques that utilize other features to deal with fingerprint images captured by solid-state sensors. This paper presents a new fingerprint matching technique based on fingerprint ridge features. This technique was assessed on the MSU-VERIDICOM database, which consists of fingerprint impressions obtained from 160 users (4 impressions per finger) using a solid-state sensor. The combination of ridge-based matching scores computed by the proposed ridge-based technique with minutia-based matching scores leads to a reduction of the false non-match rate by approximately 1.7% at a false match rate of 0.1%.</abstract>
		<language>en</language>
		<targetfile>MaranaA_fingerprint.pdf</targetfile>
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		<url>http://sibgrapi.sid.inpe.br/rep-/sid.inpe.br/banon/2005/07.05.21.20</url>
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